Industrial Engineering Workflow Automation

AI agents and physical AI are shifting industrial automation from equipment supply to autonomous, self-optimizing systems. The most mature vendors are moving from pilots to production, with robots navigating complex environments and digital twins optimizing the value chain. This CB Insights brief gives a good view of where the top 20 industrial automation companies stand on AI maturity. Three key trends. 1. Leaders like Siemens Industry and ABB are linking AI systems across design, logistics, manufacturing, and maintenance creating compounding benefits. 2. Optimization dominates near-term priorities, while digital twins are emerging as the backbone for connecting hardware and software. 3. Partnerships with tech companies like Microsoft, Google, and Nvidia are essential, but they create new dependencies that must be managed. Siemens at the top of the ranking, combining copilots, edge platforms, and digital twins. Its work with Microsoft and Nvidia expands capabilities but increases reliance on external tech. Honeywell takes a more focused approach, embedding AI into devices and workflows. Its Qualcomm partnership highlights product-level integration over broad system building. ABB advances through its OmniCore platform and acquisitions such as Sevensense and SensorFact, blending robotics, software, and energy management. Schneider Electric pushes AI in energy management, using digital twins and partnerships with Nvidia, Microsoft, and Itron to extend from factory optimization into grid intelligence. The path forward in industrial AI is moving beyond pilots or isolated tools. It will depend on how well vendors embed AI into their platforms, link technologies across domains, and balance the benefits of external partners with the need for strategic independence. Those that will get it right will turn AI from experimentation into durable advantage. Just as critical is how their customers adopt these technologies. Industrial firms must shift from isolated use cases to embedding AI in design, production, energy, and logistics. Success requires not only advanced tools, but also the data, skills, and processes to make AI scale in complex operations.

This is the Boeing 737 wheel well. And it’s closer to a spacecraft than most people realize. Thousands of parts operating in a volume smaller than a walk-in closet. Hydraulic systems running at maximum possible psi. Thermal swings, vibration, contamination, human maintenance variables all at once. Failure tolerance? Essentially zero. What’s remarkable isn’t the complexity. It’s that this system works tens of millions of flight hours globally. Much of this engineering in the legacy aircraft still relies on static models, fragmented simulations, and experience locked in people’s heads. This is where digital twins + AI become mission-critical. Not dashboards. Not buzzwords. But living system models that: • Predict fatigue before it manifests • Correlate anomalies across entire fleets • Simulate maintenance actions before technicians touch hardware • Optimize mass, routing, and reliability before first article The leaders in this space already know this: Future advantage isn’t just better hardware it’s systems intelligence at scale. The next leap in aerospace , space & defense won’t look dramatic. It will look like fewer surprises. #AerospaceEngineering #SpaceSystems #MissionAssurance #DigitalEngineering #DigitalTwin #AIinAerospace #SystemsEngineering #Defense

In 2026, pill counting isn’t just a mechanical process anymore — it’s becoming intelligent. Would you agree? Today’s high-precision pill counters combine computer vision + AI to deliver speed, accuracy, and consistency that simple sensors can’t match: 🔍 AI-Enabled Vision Systems • AI vision inspects pills, packaging defects, labels and counts with >99.5% accuracy, reducing counting errors and regulatory risks. (jidoka-tech.ai) • Camera-based inspection systems are being used in ~40% of modern pharmaceutical quality control lines. (Gitnux) 📊 Operational Impact Across Pharma • AI in quality control reduces defects and error rates by 15–40%, increasing throughput and lowering waste. • Predictive maintenance powered by AI has cut equipment downtime by up to 45% in pharma plants. • AI-driven automation is projected to handle ~40% of manufacturing processes by 2027 — a massive shift toward autonomous operations. 📈 Adoption & Market Growth Signals • Nearly 70% of pharmaceutical companies report using AI in some capacity. (IntuitionLabs) • The global AI-in-pharma market is projected to grow from ~$4.35B in 2025 to ~$25.7B by 2030. (IntuitionLabs) What the Future Holds 📦 Smart Counting + Dynamic Learning AI will soon train itself on new pill shapes, coatings, and packaging formats — reducing calibration time and manual setup. 🤖 Integrated Quality & IoT AI systems will connect with robots, MES/ERP systems, and digital twins to: • Automatically adjust feed rates for consistent output • Predict defects before they occur • Deliver real-time audit trails for regulators 📉 Autonomous Production Lines In the next decade: • Vision AI + machine learning will automate entire QC chains • Continuous manufacturing with AI control will cut batch cycle times • Real-time release testing will replace sampling-based checks AI isn’t just a trend — it’s the backbone of Industry 4.0 pharma manufacturing. Bottom line: AI has moved from pilot projects to core operational tools — and in systems like pill counting, it’s already delivering measurable accuracy gains and efficiency improvements. The future won’t just count pills faster — it’ll ensure quality, compliance, and resilience at scale. #Pharma #AI #Automation #ComputerVision #QualityControl #Industry40 #DigitalTransformation #innovation

🛑 The traditional DMAIC cycle is dead. Here is exactly what replaced it. If your DMAIC cycle still relies on manual data sampling and static spreadsheets, you are leaving massive efficiency gains on the table. We are entering the era of Quality 4.0. Here is how artificial intelligence is completely rewiring process improvement: ➡️ DEFINE (NLP-Powered Scoping): Natural Language Processing now analyzes customer complaints and incident tickets, automatically drafting problem statements. This alone can reduce phase effort by 50%. ➡️ MEASURE (Real-Time IoT): Smart sensors have replaced manual sampling. We are now establishing accurate performance baselines in hours using petabytes of data. ➡️ ANALYZE (Deep Pattern Recognition): Machine learning catches the non-linear correlations and micro-defects that human eyes and basic statistics miss, uncovering the true root causes. ➡️ IMPROVE (Digital Twin Simulations): AI agents use reinforcement learning to test thousands of improvement scenarios in a virtual model, optimizing without ever halting actual production. ➡️ CONTROL (Self-Healing Systems): Real-time dashboards are transitioning to autonomous systems that predict failure and adjust parameters instantly to maintain quality. The quantifiable impact is massive: 30% to 50% faster project cycles, up to a 40% reduction in defects, and significantly less operational waste. But it is not plug-and-play. The transition requires overcoming a real skills gap, cleaning up data infrastructure, and most importantly, breaking down cultural resistance to trusting automated insights. The methodology remains, but the execution has evolved. Which phase of the AI-powered DMAIC cycle do you think is the hardest for organizations to implement today? Let's discuss in the comments below! 👇

Securing the Invisible: Cybersecurity Challenges in Smart Manufacturing Last year, a European automotive plant faced a production halt that lasted nearly a week. The cause was not a broken robot arm but a ransomware attack that locked the SCADA servers running the assembly line. The impact rippled through suppliers, deliveries, and customer orders. This was a wake-up call: in the era of smart manufacturing, cyber risk is no longer an IT problem, it is an operational crisis. Factories are undergoing a deep transformation. Industrial Internet of Things, digital twins, predictive maintenance, and AI-driven analytics promise efficiency. Yet every new PLC, sensor, and cloud interface expands the attack surface. Unlike IT networks, plants run 24/7 with minimal tolerance for downtime. A single compromised controller can halt production, with losses climbing by the hour. The convergence of IT and OT makes this more complex. IT can be patched weekly, but many OT devices run legacy firmware untouched for years because a reboot may interrupt production. This asymmetry is exploited by attackers who move laterally from corporate systems into plant floors, abusing outdated protocols and weak segmentation. Standards are beginning to address these gaps. IEC 62443 promotes defense-in-depth through zoning and conduits that isolate control networks from enterprise IT. NIS2 in Europe forces essential manufacturers to strengthen resilience and report incidents. ISO 27001, traditionally IT-focused, is increasingly combined with OT frameworks to unify governance and compliance. The response cannot be purely technical. Zero Trust principles are reaching the factory floor, where strict access control applies even to engineers connecting remotely. Security operation centers are learning to monitor not only servers but also industrial traffic. More importantly, boards now understand that downtime caused by a cyberattack is a financial event with direct impact on revenue and reputation. The future of smart factories depends on building resilience as much as efficiency. Cybersecurity is no longer an afterthought but a design principle. Every connected device is both a source of data and a potential entry point. The companies embedding security into production systems today will not only avoid shutdowns but also secure their place in tomorrow’s global supply chain. References • IEC 62443 Industrial Security Standards – https://lnkd.in/dFtHdHAk • EU NIS2 Directive Overview – https://lnkd.in/dfexNjUn • ISO/IEC 27001 Information Security – https://lnkd.in/dtRG_ntE #OTsecurity #SmartManufacturing #IEC62443 #NIS2 #ZeroTrust #Industry40 #CyberResilience #SCADA #IIoT

As we close out 2025, I’ve been reflecting on the seismic shifts that defined industry, and what they signal for the future. 2025 was a year of compressed transformation. Persistent volatility in energy prices, supply chains, and labor markets accelerated adoption of IoT, AI, edge computing, and 5G. These technologies are no longer optional, they’re the backbone of modern industrial ecosystems. Analysts confirm this trajectory: 🔹 Deloitte reports that 80% of manufacturing executives plan to allocate 20% or more of their improvement budgets to smart manufacturing initiatives, prioritizing real-time visibility and predictive maintenance.  🔹 McKinsey & Company finds that 88% of companies now use AI in at least one function, but scaling remains a challenge - high performers redesign workflows to unlock growth and innovation.  🔹 Market forecasts show industrial automation growing from $206B in 2024 to $378B by 2030 (10.8% CAGR), driven by Industry 4.0, and AI integration.  🔹 Edge computing is surging too, expected to reach $45B by 2033, enabling low-latency analytics and predictive quality control. What does this mean for our industry? Automation is becoming open, software-defined, and decoupled from proprietary hardware, creating a foundation for adaptability, sustainability, and resilience. AI is moving from pilot projects to embedded intelligence, powering predictive maintenance, autonomous operations, and sustainability gains. At Schneider Electric, we see this every day: open, software-defined automation unlocks innovation through openness, interoperability, and flexibility, enabling manufacturers to scale faster and respond dynamically to market shifts. Looking ahead: AI will not just augment operations, it will redefine competitive advantage. From generative design to autonomous workflows, the next wave of industrial transformation is already here. 👉 What are your reflections on 2025, and where do you see the biggest opportunities in 2026 and beyond?  

Reflections and Insights: 2024 and Beyond In 2024, I learned that the most impactful transitions are not departures but transformations. As I stepped back from operational roles, I observed a pivotal shift I had long anticipated: mobile robotics have moved beyond being tactical tools to becoming strategic necessities, especially in public safety and defense. This year underscored four critical insights into our industry’s evolution: 1) The integration of mobile robotics within the Tactical Bubble is no longer optional—it’s essential for modern operations. 2) Private mesh networks (MANET) are solidifying their role as the backbone of reliable tactical communications. 3) Bridging the gap between technical capabilities and tactical operations remains our greatest challenge—and our greatest opportunity. 4) It's not just hardware; proper software (from AI to TAK, to autonomy) are the key to fully leveraging the benefits of uncrewed systems in the air, on the ground, on water and sub water. Key Developments Shaping Our Industry in 2024: Deployment and training of advanced mobile robotics across multiple agencies. Seamless integration of air, ground, and maritime robotics into unified tactical operations. Transformation of the Tech/Tac Bubble concept into actionable, real-world implementations. Significant industry shifts in military drone and mobile robotics capabilities amidst growing competition. Looking Ahead to 2025 While I didn’t initially expect to see this new year, I’ve made it here—and my focus remains steadfast. As I continue to scale back operational roles, my efforts will center on advancing mobile robotics innovation through strategic advisory and knowledge sharing. Key projects I’ve nurtured for years are being transitioned to capable individuals and entities, ensuring they remain aligned with the industry's pressing needs: standardization, immersive training, connectivity, and user-friendly solutions. To the global public safety community, defense sector, and mobile robotics innovators and manufacturers: The technology is proven. The infrastructure is advancing. We have validated countless claims and use cases. Now, the focus must shift to proper implementation, selecting the right hardware and software, ensuring comprehensive tactical training, and maintaining data-driven validation of claims. Together, we are shaping the future of mobile robotics, ensuring they serve as a force multiplier for safety, security, and innovation. Wishing you all a safe start into 2025 and a year of health, success, passion and the ability to stay grounded. #UAVsForGood #MobileRobotics #PublicSafety #TacBubble #Drones #UAVs #Training #2024Review #2025Forecast Image courtesy of FLYMOTION

We were standing in the middle of one of our production halls. Machines humming. People focused. And one laptop screen showing us something crucial: our energy reality. Mathias Weßelmann and I weren’t looking at a dashboard for the sake of it. We were looking at live data from our Energy Management Service Proficloud.io. It didn’t just show consumption—it revealed patterns, inefficiencies, and opportunities. This system connects machines, infrastructure, and buildings into one transparent energy landscape. And ISO 50001 gives us a solid framework for this. But the real value comes when we bring it to life with digital tools. Tools that don’t just collect data, but help us understand where we’re wasting energy, where we’re efficient, and where we can do better. That’s what our Energy Management Service is about. It connects the dots between data, people, and action. Real-time insights allow us to act immediately, not wait for monthly reports. That’s a shift—from reactive to proactive operations. And it supports our sustainability goals without slowing us down. How are you approaching energy management in your operations? Are you using live data or still relying on manual tracking? I’d be interested to hear what’s working for you and where you see room for improvement. Energy efficiency is becoming a strategic capability. Not because it’s required, but because it makes us better. Better at making decisions, better at reducing costs, better at building resilient operations. And that’s exactly what industrial transformation demands. And sometimes, it starts with two people, one laptop, and the willingness to look closer.

⏳ Your quarterly access review takes 40 hours across 6 people. Meanwhile, your IAM team already has real-time access analytics, automated workflows, and comprehensive audit trails. Most teams build parallel compliance infrastructure: custom AD scripts, spreadsheet workflows, separate tables. You're duplicating work whilst missing operational context. In the GRC Engineer this week, you're getting GRC Engineering, in practice! The complete methodology for automating quarterly access reviews through existing IAM infrastructure. 🔹 Practical steps: Map IAM capabilities → Identify integration points → Design data pipelines → Build enhanced workflows → Implement reporting 🔹 Real results: 85% time reduction (40→6 hours), 95% manager response rate, automated audit evidence 🔹 Vibe coding integration: When you understand existing infrastructure, your AI prompts become systematic rather than generic. Instead of "build an access review dashboard," you can specify exact APIs, authentication methods, and integration requirements. 🔹 SRE-inspired metrics: Move beyond "100% of access reviews completed" to meaningful measurements like "mean time to detect access anomalies: 12 hours" and "95% of inappropriate access removed within 48 hours" 🔹 No stakeholder disruption: Managers use the same self-service portal they already know, IT maintains existing ServiceNow workflows, and security teams keep their operational processes intact - compliance enhancement without organisational chaos. Also in this week's entry: 📊 Market consolidation: SecurityScorecard's HyperComply acquisition reflects the TPRM-driven evolution of GRC platforms. You'll get my analysis on this! 📖 Framework evolution: Shoutout to Justin Pagano's analysis of SOC 2's structural problems and his ALCOVE framework proposal and what I think about his great blog post! Tell me what you think of the newsletter this week, link in the comments ⬇️ Shoutout to Tines for partnering on this week's entry of the GRC Engineer! #GRCEngineering #AccessManagement #ComplianceAutomation